MEPS vs. NHEA

Written By: Jason Shafrin
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Dec•
20•11

Many researchers use household data sources to examine a variety of hypothesis. The use of household data has many benefits including allowing for more detailed socioeconomic information (e.g., education, income) beyond what is contained in administrative claims files. One drawback of household data is that extrapolations made from household survey data may not match national estimates.

For instance, this article examines how to align the Medical Expenditure Panel Survey (MEPS) to aggregate U.S. benchmarks provided in the National Health Expenditure Accounts (NHEA). Today, I review some of these adjustments.

The article by Selden and Sing (2008) compares NHEA Personal Health Care (PHC) expenditures against MEPS expenditures. Whereas total NHEA in the U.S. was $1.603 trillion in 2003, PHC was only $1.341 trillion since it excludes administrative costs, public health, research, and construction, none of which are captured by MEPS. Using the PHC as the starting point, here are some other key differences between the MEPS and NHEA PHC measure.

Institutionalized population and active military. PHC includes these individuals, but MEPS excludes these individuals.

Medicaid capitated payments. The authors “…modified the NHEA allocation of capitated Medicaid payments across types of service using the MEPS expenditure distribution, rather than the fee-for-service Medicaid distribution used in the construction of NHEA. This adjustment shifted expenditures from Medicaid Hospital to Medicaid Physician.”

Drug Rebates. NHEA includes rebates public insurance entities receive from pharmaceutical companies. These rebates are not captured in MEPS. The authors remove drug rebates from the NHEA PHC estimates.

Medicaid/CHIP underreporting. Like most household surveys, the MEPS data contains fewer observations of individuals stating that they have Medicaid or Children’s Health Insurance Program (CHIP) coverage than is the case when these figures are reported in administrative data. To correct for this underreporting, the authors used “a 10 percent upweighting of Medicaid and SCHIP recipients, using a raking post-stratification to preserve the MEPS distribution of poverty level, age, sex, Medicare enrollment and uninsurance.”

Underreporting of high cost cases. The authors cite other research (Zuvekas, Cohen and Pylypchuk, 2005; Zuvekas, Olin, 2009) which claim that MEPS underreports high cost cases. This could be due in part because severely ill individuals may be have higher attrition rates. Thus, the authors modify the MEPS sampling weights to increase the prevalence of high-cost cases. They do this using a partial non-response model. “Our upweighting strategy targets the top three percent of the expenditure distribution in each of four (hierarchically defined) coverage groups: ever on Medicare, ever on non-Medicare Medicaid and SCHIP, ever on Private, and full-year uninsured. A raking post-stratification was implemented to preserve MEPS distributions by age, sex, race/ethnicity, and poverty level (along with coverage). The average increase in weight was 18.1 percent…”

Laboratory Tests. “One area in which MEPS is particularly low is separately-billed laboratory tests, the number and financing of which are difficult to ascertain either from household respondents or from follow-back visits to providers ordering the tests.” The authors allocated that additional lab spending test to individuals in a proportional fashion based on each individual’s use of physician services.

Other adjustments. For the remaining adjustments, the authors simply scaled the MEPS amounts to match the NHEA figures.

Adjusting MEPS to match NHEA definition of medical expenditures

The list above describes how to calibrate MEPS to match NHEA figures for a MEPS-based definition of medical expenditures. However, the NHEA PHC figures include some expenditures which are not included in MEPS. These costs include:

Non-medical assistance with activities of daily living. These costs are born mostly by Medicaid. The authors allocated these costs in proportion to home health care by source of payment.

Hospital Subsidies. These include Medicare and Medicaid disproportionate share (DSH) payments, Medicare graduate medical education subsidies, State and local subsidies to public hospitals, Medicare retrospective adjustments and capital pass-throughs.

Public health, public research, public investment in structures and equipment.

Administrative Costs. For public programs, the authors allocate administrative costs in proportion to spending on care. For private insurance, the authors use a regression-based model which compares health expenditures against insurance premiums paid by households and employers.

Tax Expenditures. Tax expenditures include: i) the exemption of employer health insurance contributions to from employee income and payroll taxes and ii) the exemption of medical care from state and local sales taxes

Comparing MEPS to Medicare claims data

Not only does MEPS underreport utilization compared the NHEA, similar differences are found when comparing to Medicare claims data. Zuvekas and Olin (2009) find a 19 percent gap between MEPS and Medicare claims data. The The key factors driving these differentials are underreporting of ehalth care utilization by respondents and underrepresentation of high expenditure cases in MEPS.

Specifically, quantities in MEPS come from household responses. Generally, household accurately report inpatient stays, but underreport emergency department and office visits. Further, household generally estimate their out of pocket cost accurately, but most “…may not know third-party payments at all or report them inaccurately because of confusion about discounts, adjustments, and contractual arrangements.”

Underrepresentation of high cost cases about $25,000 is also a problem. Whereas the top decile spending levels in the claims data spend $23,900, in MEPS the figure is $26,700. For the top five percentiles, Medicare claims has average spending of $38,500, compared to $34,600 in MEPS.